Fix vector/matrix product (@) silently overflowing for narrow value dtypes - #44
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…types _major_matvec/_minor_matvec/_major_matmat/_minor_matmat allocated their output accumulator as values.dtype, the compact per-element storage dtype (e.g. uint16 for single-cell counts), instead of a dtype sized for the accumulated total. Contributions landing in the same output slot wrapped modulo 2**bits instead of promoting, unlike sum() which already accumulates in float64. Promote values and the other operand to their common numpy dtype (np.result_type) before running the kernels, matching the dtype promotion an equivalent dense-array product would get. Fixes #43. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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Summary
vector @ VCSRArray/VCSRArray @ vector(and the 2-D@ matrixvariants) allocated their output accumulator usingvalues.dtype— the compact stored-element dtype (e.g.uint16for single-cell counts) — instead of a dtype wide enough for the accumulated total, so results silently wrapped modulo2**bitswhilesum()(which already accumulates infloat64) stayed correct.valuesand the other operand to their commonnp.result_typebefore running the_ops.pykernels, matching the dtype promotion an equivalent dense-array product would get.Test plan
test_matmul_does_not_overflow_narrow_value_dtypeintests/test_ops.py, covering both@directions and both vector/matrix operands, for bothVCSRArrayandVCSCArray, reproducing the issue's uint16 repro.uv run pytest -q— 1662 passed, 109 skipped.uv run ruff check— clean.Fixes #43.
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